{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Turbulent Channel (Reynolds 180)\n",
    "\n",
    "The simulation of a periodic turbulent channel is also used for validation of a multilevel domain. A friction Reynolds number of 180 is fixed for both cases. The pressure gradient is estabilished through a constant body force."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:45:38.270192Z",
     "iopub.status.busy": "2026-06-29T17:45:38.270122Z",
     "iopub.status.idle": "2026-06-29T17:45:38.744994Z",
     "shell.execute_reply": "2026-06-29T17:45:38.744591Z"
    }
   },
   "outputs": [],
   "source": [
    "from nassu.cfg.model import ConfigScheme\n",
    "\n",
    "filename = \"validation/turbulence/02_turbulent_channel_flow/02_turbulent_channel_flow.nassu.yaml\"\n",
    "\n",
    "sim_cfgs = ConfigScheme.sim_cfgs_from_file_dct(filename)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The multilevel setup tries to reproduce a DNS using a optimized amount of grid nodes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:45:38.746111Z",
     "iopub.status.busy": "2026-06-29T17:45:38.745988Z",
     "iopub.status.idle": "2026-06-29T17:45:38.747683Z",
     "shell.execute_reply": "2026-06-29T17:45:38.747380Z"
    }
   },
   "outputs": [],
   "source": [
    "sim_cfg_mb = next(\n",
    "    sim_cfg\n",
    "    for (name, _), sim_cfg in sim_cfgs.items()\n",
    "    if sim_cfg.name == \"periodicTurbulentChannelMultilevel\"\n",
    ")\n",
    "sim_cfgs_use = {\"mb\": sim_cfg_mb}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Functions to use for turbulence channel processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:45:38.748504Z",
     "iopub.status.busy": "2026-06-29T17:45:38.748414Z",
     "iopub.status.idle": "2026-06-29T17:45:39.355309Z",
     "shell.execute_reply": "2026-06-29T17:45:39.354951Z"
    }
   },
   "outputs": [],
   "source": [
    "import pathlib\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import nassu.viz as common\n",
    "\n",
    "common.use_style()\n",
    "\n",
    "\n",
    "def get_experimental_profiles(reynolds_tau: float) -> dict[str, pd.DataFrame]:\n",
    "    files_tau: dict[float, dict[str, str]] = {\n",
    "        142: {\n",
    "            \"ux\": \"Re_tau_142_u_avg.csv\",\n",
    "            \"ux_rms\": \"Re_tau_142_u_rms.csv\",\n",
    "            \"uy_rms\": \"Re_tau_142_v_rms.csv\",\n",
    "            \"uz_rms\": \"Re_tau_142_w_rms.csv\",\n",
    "        },\n",
    "        520: {\n",
    "            \"ux\": \"Re_tau_520_u_avg.csv\",\n",
    "            \"ux_rms\": \"Re_tau_142_u_rms.csv\",\n",
    "        },\n",
    "    }\n",
    "\n",
    "    files_get = files_tau[reynolds_tau]\n",
    "    vals_exp: dict[str, pd.DataFrame] = {}\n",
    "    for name, comp_file in files_get.items():\n",
    "        filename = (\n",
    "            pathlib.Path(\"validation/turbulence/02_turbulent_channel_flow/reference\") / comp_file\n",
    "        )\n",
    "        df = pd.read_csv(filename, delimiter=\",\")\n",
    "        vals_exp[name] = df\n",
    "    return vals_exp\n",
    "\n",
    "\n",
    "# One cached wall-normal (y) centre-line probe per simulation's statistics\n",
    "# export, reused for every macroscopic instead of re-probing per call.\n",
    "_line_probes: dict[str, common.LineProbe] = {}\n",
    "\n",
    "\n",
    "def _line_probe(sim_cfg) -> common.LineProbe:\n",
    "    if sim_cfg.name not in _line_probes:\n",
    "        ds = sim_cfg.domain.domain_size\n",
    "        _line_probes[sim_cfg.name] = common.LineProbe.from_export(\n",
    "            sim_cfg.output.exports[\"default_stats\"].volumes[\"default_stats\"].stats,\n",
    "            sim_cfg.n_steps + 1,\n",
    "            (ds.x // 2, 0, ds.z // 2),\n",
    "            (ds.x // 2, ds.y - 1, ds.z // 2),\n",
    "            ds.y,\n",
    "        )\n",
    "    return _line_probes[sim_cfg.name]\n",
    "\n",
    "\n",
    "def get_macr_compressed(sim_cfg, macr_name: str, is_2nd_order: bool) -> np.ndarray:\n",
    "    probe = _line_probe(sim_cfg)\n",
    "    ds = sim_cfg.domain.domain_size\n",
    "    # Normalized wall-normal position of each sample (data is cell centered in the vtm).\n",
    "    norm_pos = (probe.sample_points[:, 1] + 0.5) / (ds.y + 1)\n",
    "    name = macr_name if not is_2nd_order else f\"{macr_name}_2nd\"\n",
    "    return np.array([norm_pos, probe.sample(name)])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results\n",
    "\n",
    "The average velocity profile is shown for the case. It can be a good approximation from reference results for the multilevel case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:45:39.356653Z",
     "iopub.status.busy": "2026-06-29T17:45:39.356517Z",
     "iopub.status.idle": "2026-06-29T17:45:39.946452Z",
     "shell.execute_reply": "2026-06-29T17:45:39.946097Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Despite the reynolds value being 180, the experimental data for 142 and 180 is pretty much the same\n",
    "reynolds_tau = 142\n",
    "# Friction velocity implied by the body force and the channel half-height\n",
    "# (delta = domain_size.y / 2); replaces the hand-typed u_ref literal.\n",
    "u_ref = common.friction_velocity(\n",
    "    sim_cfg_mb, geometry=\"channel\", length=sim_cfg_mb.domain.domain_size.y // 2\n",
    ")\n",
    "\n",
    "fig, ax = common.fig_single()\n",
    "\n",
    "for i, sim_cfg in enumerate(sim_cfgs_use.values()):\n",
    "    height_scale = common.wall_units_scale(sim_cfg, u_ref)\n",
    "\n",
    "    analytical_values = get_experimental_profiles(reynolds_tau)\n",
    "\n",
    "    macr_compr = get_macr_compressed(sim_cfg, \"ux\", is_2nd_order=False)\n",
    "    y = macr_compr[0].copy()\n",
    "    ux_avg = macr_compr[1].copy()\n",
    "\n",
    "    ux_avg /= u_ref\n",
    "    y *= height_scale * sim_cfg.domain.domain_size.y\n",
    "\n",
    "    exp_y = analytical_values[\"ux\"][\"y+\"]\n",
    "    exp_ux_avg = analytical_values[\"ux\"][\"u/u*\"]\n",
    "\n",
    "    ax.plot(\n",
    "        y,\n",
    "        ux_avg,\n",
    "        **common.markers.sim_line(linestyle=\"--\"),\n",
    "        label=f\"AeroSim N={sim_cfg.domain.domain_size.x}\",\n",
    "    )\n",
    "    ax.plot(exp_y, exp_ux_avg, **common.markers.exp(shape=\"o\"), label=\"Reference\")\n",
    "\n",
    "    ax.set_title(\"Multilevel\")\n",
    "\n",
    "    ax.legend()\n",
    "    ax.set_xlim(1, 160)\n",
    "    ax.set_xscale(\"symlog\")\n",
    "    ax.set_ylabel(\"$u/u*$\")\n",
    "    ax.set_xlabel(\"$y^+$\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show(fig)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The results of the ${\\mathrm{u_{rms}}}$ velocity profiles shown below also indicate a good representation with the multilevel approach."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:45:39.962743Z",
     "iopub.status.busy": "2026-06-29T17:45:39.962641Z",
     "iopub.status.idle": "2026-06-29T17:45:40.033412Z",
     "shell.execute_reply": "2026-06-29T17:45:40.033090Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 570x570 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(5.7, 5.7))\n",
    "\n",
    "vel_name_map = {\"ux\": \"u\", \"uy\": \"v\", \"uz\": \"w\"}\n",
    "vel_colors = {\"ux\": common.colors.sim, \"uy\": common.colors.blue, \"uz\": common.colors.green}\n",
    "\n",
    "for i, sim_cfg in enumerate(sim_cfgs_use.values()):\n",
    "    for macr_name in (\"ux\", \"uy\", \"uz\"):\n",
    "        macr_compr_rms = get_macr_compressed(sim_cfg, macr_name, is_2nd_order=True)\n",
    "        macr_compr_avg = get_macr_compressed(sim_cfg, macr_name, is_2nd_order=False)\n",
    "\n",
    "        y = macr_compr_rms[0].copy()\n",
    "        vel_2nd = macr_compr_rms[1].copy()\n",
    "        vel_avg = macr_compr_avg[1].copy()\n",
    "        vel_rms = (vel_2nd - vel_avg**2) ** 0.5\n",
    "\n",
    "        vel_rms /= u_ref\n",
    "        y *= height_scale * sim_cfg.domain.domain_size.y\n",
    "        # Remove wall value\n",
    "        vel_rms = vel_rms[1:]\n",
    "        y = y[1:]\n",
    "\n",
    "        c = vel_colors[macr_name]\n",
    "        name_vel = vel_name_map[macr_name]\n",
    "        df = analytical_values[f\"{macr_name}_rms\"]\n",
    "        exp_y = df[\"y+\"]\n",
    "        exp_rms = df[f\"{name_vel}'/u*\"]\n",
    "\n",
    "        ax.plot(\n",
    "            y,\n",
    "            vel_rms,\n",
    "            marker=\"x\",\n",
    "            linestyle=\"none\",\n",
    "            color=c,\n",
    "            markeredgewidth=1.7,\n",
    "            label=f\"AeroSim {name_vel.upper()}\",\n",
    "        )\n",
    "        ax.plot(\n",
    "            exp_y,\n",
    "            exp_rms,\n",
    "            marker=\"o\",\n",
    "            fillstyle=\"none\",\n",
    "            linestyle=\"none\",\n",
    "            color=c,\n",
    "            markeredgewidth=1.7,\n",
    "            label=f\"Ref. {name_vel.upper()}\",\n",
    "        )\n",
    "\n",
    "    ax.set_title(\"Multilevel\")\n",
    "\n",
    "    ax.legend()\n",
    "    ax.set_xlim(0, 80)\n",
    "    ax.set_xlabel(\"$y^+$\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Flow field\n",
    "\n",
    "Instantaneous velocity magnitude on the channel planes (`plane_series`): the streamwise / wall-normal mid-plane and the wall-parallel plane inside the refined wall block (y+ ~ 15)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:45:40.034313Z",
     "iopub.status.busy": "2026-06-29T17:45:40.034228Z",
     "iopub.status.idle": "2026-06-29T17:45:40.283665Z",
     "shell.execute_reply": "2026-06-29T17:45:40.283274Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[0m\u001b[33m2026-06-29 14:45:40.071 (   1.311s) [    7FF1B0D77740]vtkXOpenGLRenderWindow.:1460  WARN| bad X server connection. DISPLAY=\u001b[0m\n",
      "/tmp/ipykernel_1979898/3063530119.py:31: UserWarning: Using static image for notebook display.\n",
      "Install trame for interactive backends: pip install \"pyvista[jupyter]\"\n",
      "  plotter.show()\n"
     ]
    },
    {
     "data": {
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",
      "image/png": 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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=2080x260>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from nassu import viz\n",
    "\n",
    "viz.enable_offscreen()\n",
    "\n",
    "PANEL = (1040, 260)\n",
    "cfg = sim_cfgs[\"periodicTurbulentChannelMultilevel\", 0]\n",
    "domain = (384.0, 96.0, 96.0)\n",
    "\n",
    "panels = [\n",
    "    viz.Panel(\n",
    "        \"mid-channel\",\n",
    "        viz.PlaneSource.from_cfg(cfg, series=\"plane_series\", plane=\"mid_channel\"),\n",
    "        viz.frame_domain(domain, \"z\", panel=PANEL, slice_coord=48.0),\n",
    "    ),\n",
    "    viz.Panel(\n",
    "        \"near-wall (y+ ~ 15)\",\n",
    "        viz.PlaneSource.from_cfg(cfg, series=\"plane_series\", plane=\"near_wall\"),\n",
    "        viz.frame_domain(domain, \"y\", panel=PANEL, slice_coord=4.0),\n",
    "    ),\n",
    "]\n",
    "steps = [panels[0].source.steps[-1]]\n",
    "plotter = viz.render_grid(\n",
    "    panels,\n",
    "    steps=steps,\n",
    "    scalar=\"u_mag\",\n",
    "    cmap=\"viridis\",\n",
    "    clim=(0.0, 0.12),\n",
    "    bar_title=\"|u|\",\n",
    "    panel_size=PANEL,\n",
    ")\n",
    "plotter.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:45:40.285679Z",
     "iopub.status.busy": "2026-06-29T17:45:40.285602Z",
     "iopub.status.idle": "2026-06-29T17:45:40.329073Z",
     "shell.execute_reply": "2026-06-29T17:45:40.328810Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Version:"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.0.1a0"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Commit hash:"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "50dc5112a00ba586bcdeecfde90794927e2789bf"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "sim_info = sim_cfg.output.read_info()\n",
    "\n",
    "nassu_commit = sim_info[\"commit\"]\n",
    "nassu_version = sim_info[\"version\"]\n",
    "print(\"Version:\", nassu_version)\n",
    "print(\"Commit hash:\", nassu_commit)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:45:40.329738Z",
     "iopub.status.busy": "2026-06-29T17:45:40.329660Z",
     "iopub.status.idle": "2026-06-29T17:45:40.365503Z",
     "shell.execute_reply": "2026-06-29T17:45:40.365168Z"
    }
   },
   "outputs": [
    {
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       ".output_html .il { color: #666 } /* Literal.Number.Integer.Long */</style><div class=\"highlight\"><pre><span></span><span class=\"nt\">variables</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\"># Domain size</span>\n",
       "<span class=\"w\">  </span><span class=\"nt\">ds_1</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">    </span><span class=\"nt\">x</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">512</span>\n",
       "<span class=\"w\">    </span><span class=\"nt\">y</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">128</span>\n",
       "<span class=\"w\">    </span><span class=\"nt\">z</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">128</span>\n",
       "<span class=\"w\">  </span><span class=\"nt\">ds_2</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">    </span><span class=\"nt\">x</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">384</span>\n",
       "<span class=\"w\">    </span><span class=\"nt\">y</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">96</span>\n",
       "<span class=\"w\">    </span><span class=\"nt\">z</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">96</span>\n",
       "\n",
       "<span class=\"w\">  </span><span class=\"c1\"># Equation-based (&quot;cold&quot;) start - self-contained, no external</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\"># artefact. The streamwise field is an analytic Reichardt mean</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\"># profile mirrored across both walls (wall distance in viscous</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\"># units y+ = (u*/nu) * min(y, NY - y)), scaled by the friction</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\"># velocity u*, seeded with wall-enveloped multi-mode sinusoidal</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\"># perturbations (streamwise streaks plus cross-flow rolls carrying</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\"># wall-normal velocity) at ~10% intensity to break the x/z symmetry</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\"># and trip transition to turbulence. The sin(pi*y/NY) envelope</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\"># vanishes at both no-slip walls. The scalar is initialised</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\"># separately via its `initial_field` ramp.</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\">#</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\"># Per-domain friction velocity u* and inner-scale coefficient</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\"># y+/lattice = u*/nu, with nu = cs^2 (tau - 0.5):</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\">#   ds_1: Re_tau 142, tau=0.5074 -&gt; nu=2.467e-3, u*=0.0054962, u*/nu=2.228</span>\n",
       "<span class=\"w\">  </span><span class=\"c1\">#   ds_2: Re_tau 180, tau=0.5042 -&gt; nu=1.400e-3, u*=0.00525, u*/nu=3.75</span>\n",
       "<span class=\"w\">  </span><span class=\"nt\">us_1</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0.0054962</span>\n",
       "<span class=\"w\">  </span><span class=\"nt\">yp_1</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">2.228</span>\n",
       "<span class=\"w\">  </span><span class=\"nt\">us_2</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0.00525</span>\n",
       "<span class=\"w\">  </span><span class=\"nt\">yp_2</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">3.75</span>\n",
       "<span class=\"w\">  </span><span class=\"nt\">init</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">    </span><span class=\"nt\">ds_1</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">ux</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!sub</span><span class=\"w\"> </span><span class=\"s\">&quot;${us_1}</span><span class=\"nv\"> </span><span class=\"s\">*</span><span class=\"nv\"> </span><span class=\"s\">(2.5*log(1</span><span class=\"nv\"> </span><span class=\"s\">+</span><span class=\"nv\"> </span><span class=\"s\">0.41*${yp_1}*min(y,</span><span class=\"nv\"> </span><span class=\"s\">${ds_1.y}</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">y))</span><span class=\"nv\"> </span><span class=\"s\">+</span><span class=\"nv\"> </span><span class=\"s\">7.8*(1</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">exp(-${yp_1}*min(y,</span><span class=\"nv\"> </span><span class=\"s\">${ds_1.y}</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">y)/11)</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">(${yp_1}*min(y,</span><span class=\"nv\"> </span><span class=\"s\">${ds_1.y}</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">y)/11)*exp(-${yp_1}*min(y,</span><span class=\"nv\"> </span><span class=\"s\">${ds_1.y}</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">y)/3)))</span><span class=\"nv\"> </span><span class=\"s\">+</span><span class=\"nv\"> </span><span class=\"s\">0.010*sin(pi*y/${ds_1.y})*cos(2*pi*5*z/${ds_1.z})</span><span class=\"nv\"> </span><span class=\"s\">+</span><span class=\"nv\"> </span><span class=\"s\">0.006*sin(pi*y/${ds_1.y})*sin(2*pi*3*x/${ds_1.x})*cos(2*pi*4*z/${ds_1.z})&quot;</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">uy</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!sub</span><span class=\"w\"> </span><span class=\"s\">&quot;0.006*sin(pi*y/${ds_1.y})*sin(2*pi*3*x/${ds_1.x})*cos(2*pi*4*z/${ds_1.z})</span><span class=\"nv\"> </span><span class=\"s\">+</span><span class=\"nv\"> </span><span class=\"s\">0.004*sin(pi*y/${ds_1.y})*sin(2*pi*2*x/${ds_1.x})*sin(2*pi*3*z/${ds_1.z})&quot;</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">uz</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!sub</span><span class=\"w\"> </span><span class=\"s\">&quot;0.006*sin(pi*y/${ds_1.y})*sin(2*pi*3*x/${ds_1.x})*sin(2*pi*4*z/${ds_1.z})</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">0.004*sin(pi*y/${ds_1.y})*cos(2*pi*2*x/${ds_1.x})*cos(2*pi*3*z/${ds_1.z})&quot;</span>\n",
       "<span class=\"w\">    </span><span class=\"nt\">ds_2</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">ux</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!sub</span><span class=\"w\"> </span><span class=\"s\">&quot;${us_2}</span><span class=\"nv\"> </span><span class=\"s\">*</span><span class=\"nv\"> </span><span class=\"s\">(2.5*log(1</span><span class=\"nv\"> </span><span class=\"s\">+</span><span class=\"nv\"> </span><span class=\"s\">0.41*${yp_2}*min(y,</span><span class=\"nv\"> </span><span class=\"s\">${ds_2.y}</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">y))</span><span class=\"nv\"> </span><span class=\"s\">+</span><span class=\"nv\"> </span><span class=\"s\">7.8*(1</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">exp(-${yp_2}*min(y,</span><span class=\"nv\"> </span><span class=\"s\">${ds_2.y}</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">y)/11)</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">(${yp_2}*min(y,</span><span class=\"nv\"> </span><span class=\"s\">${ds_2.y}</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">y)/11)*exp(-${yp_2}*min(y,</span><span class=\"nv\"> </span><span class=\"s\">${ds_2.y}</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">y)/3)))</span><span class=\"nv\"> </span><span class=\"s\">+</span><span class=\"nv\"> </span><span class=\"s\">0.010*sin(pi*y/${ds_2.y})*cos(2*pi*5*z/${ds_2.z})</span><span class=\"nv\"> </span><span class=\"s\">+</span><span class=\"nv\"> </span><span class=\"s\">0.006*sin(pi*y/${ds_2.y})*sin(2*pi*3*x/${ds_2.x})*cos(2*pi*4*z/${ds_2.z})&quot;</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">uy</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!sub</span><span class=\"w\"> </span><span class=\"s\">&quot;0.006*sin(pi*y/${ds_2.y})*sin(2*pi*3*x/${ds_2.x})*cos(2*pi*4*z/${ds_2.z})</span><span class=\"nv\"> </span><span class=\"s\">+</span><span class=\"nv\"> </span><span class=\"s\">0.004*sin(pi*y/${ds_2.y})*sin(2*pi*2*x/${ds_2.x})*sin(2*pi*3*z/${ds_2.z})&quot;</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">uz</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!sub</span><span class=\"w\"> </span><span class=\"s\">&quot;0.006*sin(pi*y/${ds_2.y})*sin(2*pi*3*x/${ds_2.x})*sin(2*pi*4*z/${ds_2.z})</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">0.004*sin(pi*y/${ds_2.y})*cos(2*pi*2*x/${ds_2.x})*cos(2*pi*3*z/${ds_2.z})&quot;</span>\n",
       "\n",
       "<span class=\"nt\">simulations</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">  </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">name</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">periodicTurbulentChannel</span>\n",
       "<span class=\"w\">    </span><span class=\"nt\">save_path</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">./validation/turbulence/02_turbulent_channel_flow/results/</span>\n",
       "\n",
       "<span class=\"w\">    </span><span class=\"nt\">n_steps</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">600000</span>\n",
       "<span class=\"w\">    </span><span class=\"nt\">report</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">frequency</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1000</span>\n",
       "\n",
       "<span class=\"w\">    </span><span class=\"nt\">domain</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"c1\"># u* = 0.0054962 / l = 64 / ETT = l/u* = 11,644</span>\n",
       "<span class=\"w\">      </span><span class=\"c1\"># Re_tau = 142</span>\n",
       "<span class=\"w\">      </span><span class=\"c1\"># y+ = 2.228</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">domain_size</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">x</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!math</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">${ds_1.x}</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">y</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!math</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">${ds_1.y}</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">z</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!math</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">${ds_1.z}</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">block_size</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">8</span>\n",
       "\n",
       "<span class=\"w\">    </span><span class=\"nt\">data</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">exports</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">default</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">macrs</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">rho</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">u</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">S</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">interval</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">frequency</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">200000</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">lvl</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">target</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">volume</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">{}</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">outputs</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">instantaneous</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">true</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">default_stats</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">macrs</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">rho</span>\n",
       "<span class=\"w\">            </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">u</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">interval</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">frequency</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">100</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">start_step</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">300000</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">lvl</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">target</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">volume</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">{}</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">outputs</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">instantaneous</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">false</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">stats</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">              </span><span class=\"nt\">macrs_1st_order</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">                </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">rho</span>\n",
       "<span class=\"w\">                </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">u</span>\n",
       "<span class=\"w\">              </span><span class=\"nt\">macrs_2nd_order</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">                </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">u</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">plane_series</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">macrs</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">rho</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">u</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">interval</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">{</span><span class=\"nt\">frequency</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"nv\">50000</span><span class=\"p p-Indicator\">,</span><span class=\"nt\"> lvl</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"nv\">0</span><span class=\"p p-Indicator\">}</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">target</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">planes</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">              </span><span class=\"c1\"># Streamwise / wall-normal mid-plane (walls are y-normal here).</span>\n",
       "<span class=\"w\">              </span><span class=\"nt\">mid_channel</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">z</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis_pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">64</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">dist</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "<span class=\"w\">              </span><span class=\"c1\"># Wall-parallel plane in the buffer layer (y+ ~ 16):</span>\n",
       "<span class=\"w\">              </span><span class=\"c1\"># near-wall streak visualization.</span>\n",
       "<span class=\"w\">              </span><span class=\"nt\">near_wall</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">y</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis_pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">8</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">dist</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">outputs</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">instantaneous</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">true</span>\n",
       "\n",
       "<span class=\"w\">    </span><span class=\"nt\">models</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">precision</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">default</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">single</span>\n",
       "\n",
       "<span class=\"w\">      </span><span class=\"nt\">LBM</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">tau</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0.5074</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">F</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">x</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">4.72e-7</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">y</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">z</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">vel_set</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">D3Q27</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">coll_oper</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">RRBGK</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">initialization</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">equations</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">rho</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s\">&quot;1&quot;</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">ux</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!sub</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">${init.ds_1.ux}</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">uy</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!sub</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">${init.ds_1.uy}</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">uz</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!sub</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">${init.ds_1.uz}</span>\n",
       "\n",
       "<span class=\"w\">      </span><span class=\"nt\">engine</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">name</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">CUDA</span>\n",
       "\n",
       "<span class=\"w\">      </span><span class=\"nt\">BC</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">periodic_dims</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">true</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">false</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">true</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">BC_map</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">N</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">BC</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">RegularizedHWBB</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">wall_normal</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">N</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">order</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "\n",
       "<span class=\"w\">          </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">S</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">BC</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">RegularizedHWBB</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">wall_normal</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">S</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">order</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "\n",
       "<span class=\"w\">  </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">name</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">periodicTurbulentChannelMultilevel</span>\n",
       "<span class=\"w\">    </span><span class=\"nt\">save_path</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">./validation/turbulence/02_turbulent_channel_flow/results/</span>\n",
       "\n",
       "<span class=\"w\">    </span><span class=\"nt\">n_steps</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">200000</span>\n",
       "<span class=\"w\">    </span><span class=\"c1\"># u* = 0.00525 / l = 48 / ETT = l/u* = 9,150</span>\n",
       "<span class=\"w\">    </span><span class=\"c1\"># Re_tau = 180</span>\n",
       "<span class=\"w\">    </span><span class=\"c1\"># y+ = 3.75 (lvl 0)</span>\n",
       "\n",
       "<span class=\"w\">    </span><span class=\"nt\">report</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">frequency</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1000</span>\n",
       "\n",
       "<span class=\"w\">    </span><span class=\"nt\">domain</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">domain_size</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">x</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!math</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">${ds_2.x}</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">y</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!math</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">${ds_2.y}</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">z</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!math</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">${ds_2.z}</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">block_size</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">8</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">refinement</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">static</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">default</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">volumes_refine</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">              </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">start</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">0</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">0</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">0</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">end</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">384</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">8</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">96</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">lvl</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">is_abs</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">true</span>\n",
       "<span class=\"w\">              </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">start</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">0</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">88</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">0</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">end</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">384</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">96</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">96</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">lvl</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">is_abs</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">true</span>\n",
       "\n",
       "<span class=\"w\">    </span><span class=\"nt\">data</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">exports</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">default</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">macrs</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">rho</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">u</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">S</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">interval</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">frequency</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">200000</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">lvl</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">target</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">volume</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">{}</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">outputs</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">instantaneous</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">true</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">start_simul</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">macrs</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">rho</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">u</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">S</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">interval</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">end_step</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">2000</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">frequency</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">500</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">lvl</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">target</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">volume</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">{}</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">outputs</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">instantaneous</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">true</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">default_stats</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">macrs</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">rho</span>\n",
       "<span class=\"w\">            </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">u</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">interval</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">frequency</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">50</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">start_step</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">50000</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">lvl</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">target</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">volume</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">{}</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">outputs</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">instantaneous</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">false</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">stats</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">              </span><span class=\"nt\">macrs_1st_order</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">                </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">rho</span>\n",
       "<span class=\"w\">                </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">u</span>\n",
       "<span class=\"w\">              </span><span class=\"nt\">macrs_2nd_order</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">                </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">u</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">plane_series</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">macrs</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">rho</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">u</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">interval</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">{</span><span class=\"nt\">frequency</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"nv\">50000</span><span class=\"p p-Indicator\">,</span><span class=\"nt\"> lvl</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"nv\">0</span><span class=\"p p-Indicator\">}</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">target</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">planes</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">              </span><span class=\"c1\"># Streamwise / wall-normal mid-plane (walls are y-normal here).</span>\n",
       "<span class=\"w\">              </span><span class=\"nt\">mid_channel</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">z</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis_pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">48</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">dist</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "<span class=\"w\">              </span><span class=\"c1\"># Wall-parallel plane in the buffer layer (y+ ~ 15, inside the</span>\n",
       "<span class=\"w\">              </span><span class=\"c1\"># refined wall block): near-wall streak visualization. One node</span>\n",
       "<span class=\"w\">              </span><span class=\"c1\"># apart is enough - the streak spacing is ~26 nodes.</span>\n",
       "<span class=\"w\">              </span><span class=\"nt\">near_wall</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">y</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis_pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">4</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">dist</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">outputs</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">instantaneous</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">true</span>\n",
       "\n",
       "<span class=\"w\">    </span><span class=\"nt\">models</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">precision</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">default</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">single</span>\n",
       "\n",
       "<span class=\"w\">      </span><span class=\"nt\">LBM</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">tau</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0.5042</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">F</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">x</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">5.75e-7</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">y</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">z</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">vel_set</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">D3Q27</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">coll_oper</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">RRBGK</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">initialization</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">equations</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">rho</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s\">&quot;1&quot;</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">ux</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!sub</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">${init.ds_2.ux}</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">uy</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!sub</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">${init.ds_2.uy}</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">uz</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!sub</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">${init.ds_2.uz}</span>\n",
       "\n",
       "<span class=\"w\">      </span><span class=\"nt\">engine</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">name</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">CUDA</span>\n",
       "\n",
       "<span class=\"w\">      </span><span class=\"nt\">BC</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">periodic_dims</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">true</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">false</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">true</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">BC_map</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">N</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">BC</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">RegularizedHWBB</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">wall_normal</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">N</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">order</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "\n",
       "<span class=\"w\">          </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">S</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">BC</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">RegularizedHWBB</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">wall_normal</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">S</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">order</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "</pre></div>\n"
      ],
      "text/latex": [
       "\\begin{Verbatim}[commandchars=\\\\\\{\\}]\n",
       "\\PY{n+nt}{variables}\\PY{p}{:}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{} Domain size}\n",
       "\\PY{+w}{  }\\PY{n+nt}{ds\\PYZus{}1}\\PY{p}{:}\n",
       "\\PY{+w}{    }\\PY{n+nt}{x}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{512}\n",
       "\\PY{+w}{    }\\PY{n+nt}{y}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{128}\n",
       "\\PY{+w}{    }\\PY{n+nt}{z}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{128}\n",
       "\\PY{+w}{  }\\PY{n+nt}{ds\\PYZus{}2}\\PY{p}{:}\n",
       "\\PY{+w}{    }\\PY{n+nt}{x}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{384}\n",
       "\\PY{+w}{    }\\PY{n+nt}{y}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{96}\n",
       "\\PY{+w}{    }\\PY{n+nt}{z}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{96}\n",
       "\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{} Equation\\PYZhy{}based (\\PYZdq{}cold\\PYZdq{}) start \\PYZhy{} self\\PYZhy{}contained, no external}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{} artefact. The streamwise field is an analytic Reichardt mean}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{} profile mirrored across both walls (wall distance in viscous}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{} units y+ = (u*/nu) * min(y, NY \\PYZhy{} y)), scaled by the friction}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{} velocity u*, seeded with wall\\PYZhy{}enveloped multi\\PYZhy{}mode sinusoidal}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{} perturbations (streamwise streaks plus cross\\PYZhy{}flow rolls carrying}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{} wall\\PYZhy{}normal velocity) at \\PYZti{}10\\PYZpc{} intensity to break the x/z symmetry}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{} and trip transition to turbulence. The sin(pi*y/NY) envelope}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{} vanishes at both no\\PYZhy{}slip walls. The scalar is initialised}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{} separately via its `initial\\PYZus{}field` ramp.}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{} Per\\PYZhy{}domain friction velocity u* and inner\\PYZhy{}scale coefficient}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{} y+/lattice = u*/nu, with nu = cs\\PYZca{}2 (tau \\PYZhy{} 0.5):}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{}   ds\\PYZus{}1: Re\\PYZus{}tau 142, tau=0.5074 \\PYZhy{}\\PYZgt{} nu=2.467e\\PYZhy{}3, u*=0.0054962, u*/nu=2.228}\n",
       "\\PY{+w}{  }\\PY{c+c1}{\\PYZsh{}   ds\\PYZus{}2: Re\\PYZus{}tau 180, tau=0.5042 \\PYZhy{}\\PYZgt{} nu=1.400e\\PYZhy{}3, u*=0.00525, u*/nu=3.75}\n",
       "\\PY{+w}{  }\\PY{n+nt}{us\\PYZus{}1}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0.0054962}\n",
       "\\PY{+w}{  }\\PY{n+nt}{yp\\PYZus{}1}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{2.228}\n",
       "\\PY{+w}{  }\\PY{n+nt}{us\\PYZus{}2}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0.00525}\n",
       "\\PY{+w}{  }\\PY{n+nt}{yp\\PYZus{}2}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{3.75}\n",
       "\\PY{+w}{  }\\PY{n+nt}{init}\\PY{p}{:}\n",
       "\\PY{+w}{    }\\PY{n+nt}{ds\\PYZus{}1}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{n+nt}{ux}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!sub}\\PY{+w}{ }\\PY{l+s}{\\PYZdq{}}\\PY{l+s}{\\PYZdl{}\\PYZob{}us\\PYZus{}1\\PYZcb{}}\\PY{n+nv}{ }\\PY{l+s}{*}\\PY{n+nv}{ }\\PY{l+s}{(2.5*log(1}\\PY{n+nv}{ }\\PY{l+s}{+}\\PY{n+nv}{ }\\PY{l+s}{0.41*\\PYZdl{}\\PYZob{}yp\\PYZus{}1\\PYZcb{}*min(y,}\\PY{n+nv}{ }\\PY{l+s}{\\PYZdl{}\\PYZob{}ds\\PYZus{}1.y\\PYZcb{}}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{y))}\\PY{n+nv}{ }\\PY{l+s}{+}\\PY{n+nv}{ }\\PY{l+s}{7.8*(1}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{exp(\\PYZhy{}\\PYZdl{}\\PYZob{}yp\\PYZus{}1\\PYZcb{}*min(y,}\\PY{n+nv}{ }\\PY{l+s}{\\PYZdl{}\\PYZob{}ds\\PYZus{}1.y\\PYZcb{}}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{y)/11)}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{(\\PYZdl{}\\PYZob{}yp\\PYZus{}1\\PYZcb{}*min(y,}\\PY{n+nv}{ }\\PY{l+s}{\\PYZdl{}\\PYZob{}ds\\PYZus{}1.y\\PYZcb{}}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{y)/11)*exp(\\PYZhy{}\\PYZdl{}\\PYZob{}yp\\PYZus{}1\\PYZcb{}*min(y,}\\PY{n+nv}{ }\\PY{l+s}{\\PYZdl{}\\PYZob{}ds\\PYZus{}1.y\\PYZcb{}}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{y)/3)))}\\PY{n+nv}{ }\\PY{l+s}{+}\\PY{n+nv}{ }\\PY{l+s}{0.010*sin(pi*y/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.y\\PYZcb{})*cos(2*pi*5*z/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.z\\PYZcb{})}\\PY{n+nv}{ }\\PY{l+s}{+}\\PY{n+nv}{ }\\PY{l+s}{0.006*sin(pi*y/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.y\\PYZcb{})*sin(2*pi*3*x/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.x\\PYZcb{})*cos(2*pi*4*z/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.z\\PYZcb{})}\\PY{l+s}{\\PYZdq{}}\n",
       "\\PY{+w}{      }\\PY{n+nt}{uy}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!sub}\\PY{+w}{ }\\PY{l+s}{\\PYZdq{}}\\PY{l+s}{0.006*sin(pi*y/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.y\\PYZcb{})*sin(2*pi*3*x/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.x\\PYZcb{})*cos(2*pi*4*z/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.z\\PYZcb{})}\\PY{n+nv}{ }\\PY{l+s}{+}\\PY{n+nv}{ }\\PY{l+s}{0.004*sin(pi*y/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.y\\PYZcb{})*sin(2*pi*2*x/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.x\\PYZcb{})*sin(2*pi*3*z/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.z\\PYZcb{})}\\PY{l+s}{\\PYZdq{}}\n",
       "\\PY{+w}{      }\\PY{n+nt}{uz}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!sub}\\PY{+w}{ }\\PY{l+s}{\\PYZdq{}}\\PY{l+s}{0.006*sin(pi*y/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.y\\PYZcb{})*sin(2*pi*3*x/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.x\\PYZcb{})*sin(2*pi*4*z/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.z\\PYZcb{})}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{0.004*sin(pi*y/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.y\\PYZcb{})*cos(2*pi*2*x/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.x\\PYZcb{})*cos(2*pi*3*z/\\PYZdl{}\\PYZob{}ds\\PYZus{}1.z\\PYZcb{})}\\PY{l+s}{\\PYZdq{}}\n",
       "\\PY{+w}{    }\\PY{n+nt}{ds\\PYZus{}2}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{n+nt}{ux}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!sub}\\PY{+w}{ }\\PY{l+s}{\\PYZdq{}}\\PY{l+s}{\\PYZdl{}\\PYZob{}us\\PYZus{}2\\PYZcb{}}\\PY{n+nv}{ }\\PY{l+s}{*}\\PY{n+nv}{ }\\PY{l+s}{(2.5*log(1}\\PY{n+nv}{ }\\PY{l+s}{+}\\PY{n+nv}{ }\\PY{l+s}{0.41*\\PYZdl{}\\PYZob{}yp\\PYZus{}2\\PYZcb{}*min(y,}\\PY{n+nv}{ }\\PY{l+s}{\\PYZdl{}\\PYZob{}ds\\PYZus{}2.y\\PYZcb{}}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{y))}\\PY{n+nv}{ }\\PY{l+s}{+}\\PY{n+nv}{ }\\PY{l+s}{7.8*(1}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{exp(\\PYZhy{}\\PYZdl{}\\PYZob{}yp\\PYZus{}2\\PYZcb{}*min(y,}\\PY{n+nv}{ }\\PY{l+s}{\\PYZdl{}\\PYZob{}ds\\PYZus{}2.y\\PYZcb{}}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{y)/11)}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{(\\PYZdl{}\\PYZob{}yp\\PYZus{}2\\PYZcb{}*min(y,}\\PY{n+nv}{ }\\PY{l+s}{\\PYZdl{}\\PYZob{}ds\\PYZus{}2.y\\PYZcb{}}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{y)/11)*exp(\\PYZhy{}\\PYZdl{}\\PYZob{}yp\\PYZus{}2\\PYZcb{}*min(y,}\\PY{n+nv}{ }\\PY{l+s}{\\PYZdl{}\\PYZob{}ds\\PYZus{}2.y\\PYZcb{}}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{y)/3)))}\\PY{n+nv}{ }\\PY{l+s}{+}\\PY{n+nv}{ }\\PY{l+s}{0.010*sin(pi*y/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.y\\PYZcb{})*cos(2*pi*5*z/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.z\\PYZcb{})}\\PY{n+nv}{ }\\PY{l+s}{+}\\PY{n+nv}{ }\\PY{l+s}{0.006*sin(pi*y/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.y\\PYZcb{})*sin(2*pi*3*x/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.x\\PYZcb{})*cos(2*pi*4*z/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.z\\PYZcb{})}\\PY{l+s}{\\PYZdq{}}\n",
       "\\PY{+w}{      }\\PY{n+nt}{uy}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!sub}\\PY{+w}{ }\\PY{l+s}{\\PYZdq{}}\\PY{l+s}{0.006*sin(pi*y/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.y\\PYZcb{})*sin(2*pi*3*x/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.x\\PYZcb{})*cos(2*pi*4*z/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.z\\PYZcb{})}\\PY{n+nv}{ }\\PY{l+s}{+}\\PY{n+nv}{ }\\PY{l+s}{0.004*sin(pi*y/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.y\\PYZcb{})*sin(2*pi*2*x/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.x\\PYZcb{})*sin(2*pi*3*z/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.z\\PYZcb{})}\\PY{l+s}{\\PYZdq{}}\n",
       "\\PY{+w}{      }\\PY{n+nt}{uz}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!sub}\\PY{+w}{ }\\PY{l+s}{\\PYZdq{}}\\PY{l+s}{0.006*sin(pi*y/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.y\\PYZcb{})*sin(2*pi*3*x/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.x\\PYZcb{})*sin(2*pi*4*z/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.z\\PYZcb{})}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{0.004*sin(pi*y/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.y\\PYZcb{})*cos(2*pi*2*x/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.x\\PYZcb{})*cos(2*pi*3*z/\\PYZdl{}\\PYZob{}ds\\PYZus{}2.z\\PYZcb{})}\\PY{l+s}{\\PYZdq{}}\n",
       "\n",
       "\\PY{n+nt}{simulations}\\PY{p}{:}\n",
       "\\PY{+w}{  }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{name}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{periodicTurbulentChannel}\n",
       "\\PY{+w}{    }\\PY{n+nt}{save\\PYZus{}path}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{./validation/turbulence/02\\PYZus{}turbulent\\PYZus{}channel\\PYZus{}flow/results/}\n",
       "\n",
       "\\PY{+w}{    }\\PY{n+nt}{n\\PYZus{}steps}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{600000}\n",
       "\\PY{+w}{    }\\PY{n+nt}{report}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{n+nt}{frequency}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1000}\n",
       "\n",
       "\\PY{+w}{    }\\PY{n+nt}{domain}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{c+c1}{\\PYZsh{} u* = 0.0054962 / l = 64 / ETT = l/u* = 11,644}\n",
       "\\PY{+w}{      }\\PY{c+c1}{\\PYZsh{} Re\\PYZus{}tau = 142}\n",
       "\\PY{+w}{      }\\PY{c+c1}{\\PYZsh{} y+ = 2.228}\n",
       "\\PY{+w}{      }\\PY{n+nt}{domain\\PYZus{}size}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{x}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!math}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{\\PYZdl{}\\PYZob{}ds\\PYZus{}1.x\\PYZcb{}}\n",
       "\\PY{+w}{        }\\PY{n+nt}{y}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!math}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{\\PYZdl{}\\PYZob{}ds\\PYZus{}1.y\\PYZcb{}}\n",
       "\\PY{+w}{        }\\PY{n+nt}{z}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!math}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{\\PYZdl{}\\PYZob{}ds\\PYZus{}1.z\\PYZcb{}}\n",
       "\\PY{+w}{      }\\PY{n+nt}{block\\PYZus{}size}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{8}\n",
       "\n",
       "\\PY{+w}{    }\\PY{n+nt}{data}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{n+nt}{exports}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{default}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{macrs}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{rho}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{u}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{S}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{          }\\PY{n+nt}{interval}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{frequency}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{200000}\n",
       "\\PY{+w}{            }\\PY{n+nt}{lvl}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0}\n",
       "\\PY{+w}{          }\\PY{n+nt}{target}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{volume}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{\\PYZob{}}\\PY{p+pIndicator}{\\PYZcb{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{outputs}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{instantaneous}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{true}\n",
       "\\PY{+w}{        }\\PY{n+nt}{default\\PYZus{}stats}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{macrs}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{rho}\n",
       "\\PY{+w}{            }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{u}\n",
       "\\PY{+w}{          }\\PY{n+nt}{interval}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{frequency}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{100}\n",
       "\\PY{+w}{            }\\PY{n+nt}{start\\PYZus{}step}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{300000}\n",
       "\\PY{+w}{            }\\PY{n+nt}{lvl}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0}\n",
       "\\PY{+w}{          }\\PY{n+nt}{target}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{volume}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{\\PYZob{}}\\PY{p+pIndicator}{\\PYZcb{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{outputs}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{instantaneous}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{false}\n",
       "\\PY{+w}{            }\\PY{n+nt}{stats}\\PY{p}{:}\n",
       "\\PY{+w}{              }\\PY{n+nt}{macrs\\PYZus{}1st\\PYZus{}order}\\PY{p}{:}\n",
       "\\PY{+w}{                }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{rho}\n",
       "\\PY{+w}{                }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{u}\n",
       "\\PY{+w}{              }\\PY{n+nt}{macrs\\PYZus{}2nd\\PYZus{}order}\\PY{p}{:}\n",
       "\\PY{+w}{                }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{u}\n",
       "\\PY{+w}{        }\\PY{n+nt}{plane\\PYZus{}series}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{macrs}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{rho}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{u}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{          }\\PY{n+nt}{interval}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{\\PYZob{}}\\PY{n+nt}{frequency}\\PY{p}{:}\\PY{+w}{ }\\PY{n+nv}{50000}\\PY{p+pIndicator}{,}\\PY{n+nt}{ lvl}\\PY{p}{:}\\PY{+w}{ }\\PY{n+nv}{0}\\PY{p+pIndicator}{\\PYZcb{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{target}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{planes}\\PY{p}{:}\n",
       "\\PY{+w}{              }\\PY{c+c1}{\\PYZsh{} Streamwise / wall\\PYZhy{}normal mid\\PYZhy{}plane (walls are y\\PYZhy{}normal here).}\n",
       "\\PY{+w}{              }\\PY{n+nt}{mid\\PYZus{}channel}\\PY{p}{:}\n",
       "\\PY{+w}{                }\\PY{n+nt}{axis}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{z}\n",
       "\\PY{+w}{                }\\PY{n+nt}{axis\\PYZus{}pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{64}\n",
       "\\PY{+w}{                }\\PY{n+nt}{dist}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1}\n",
       "\\PY{+w}{              }\\PY{c+c1}{\\PYZsh{} Wall\\PYZhy{}parallel plane in the buffer layer (y+ \\PYZti{} 16):}\n",
       "\\PY{+w}{              }\\PY{c+c1}{\\PYZsh{} near\\PYZhy{}wall streak visualization.}\n",
       "\\PY{+w}{              }\\PY{n+nt}{near\\PYZus{}wall}\\PY{p}{:}\n",
       "\\PY{+w}{                }\\PY{n+nt}{axis}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{y}\n",
       "\\PY{+w}{                }\\PY{n+nt}{axis\\PYZus{}pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{8}\n",
       "\\PY{+w}{                }\\PY{n+nt}{dist}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1}\n",
       "\\PY{+w}{          }\\PY{n+nt}{outputs}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{instantaneous}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{true}\n",
       "\n",
       "\\PY{+w}{    }\\PY{n+nt}{models}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{n+nt}{precision}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{default}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{single}\n",
       "\n",
       "\\PY{+w}{      }\\PY{n+nt}{LBM}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{tau}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0.5074}\n",
       "\\PY{+w}{        }\\PY{n+nt}{F}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{x}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{4.72e\\PYZhy{}7}\n",
       "\\PY{+w}{          }\\PY{n+nt}{y}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0}\n",
       "\\PY{+w}{          }\\PY{n+nt}{z}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0}\n",
       "\\PY{+w}{        }\\PY{n+nt}{vel\\PYZus{}set}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{D3Q27}\n",
       "\\PY{+w}{        }\\PY{n+nt}{coll\\PYZus{}oper}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{RRBGK}\n",
       "\\PY{+w}{      }\\PY{n+nt}{initialization}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{equations}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{rho}\\PY{p}{:}\\PY{+w}{ }\\PY{l+s}{\\PYZdq{}}\\PY{l+s}{1}\\PY{l+s}{\\PYZdq{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{ux}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!sub}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{\\PYZdl{}\\PYZob{}init.ds\\PYZus{}1.ux\\PYZcb{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{uy}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!sub}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{\\PYZdl{}\\PYZob{}init.ds\\PYZus{}1.uy\\PYZcb{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{uz}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!sub}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{\\PYZdl{}\\PYZob{}init.ds\\PYZus{}1.uz\\PYZcb{}}\n",
       "\n",
       "\\PY{+w}{      }\\PY{n+nt}{engine}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{name}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{CUDA}\n",
       "\n",
       "\\PY{+w}{      }\\PY{n+nt}{BC}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{periodic\\PYZus{}dims}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{true}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{false}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{true}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{        }\\PY{n+nt}{BC\\PYZus{}map}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{N}\n",
       "\\PY{+w}{            }\\PY{n+nt}{BC}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{RegularizedHWBB}\n",
       "\\PY{+w}{            }\\PY{n+nt}{wall\\PYZus{}normal}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{N}\n",
       "\\PY{+w}{            }\\PY{n+nt}{order}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1}\n",
       "\n",
       "\\PY{+w}{          }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{S}\n",
       "\\PY{+w}{            }\\PY{n+nt}{BC}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{RegularizedHWBB}\n",
       "\\PY{+w}{            }\\PY{n+nt}{wall\\PYZus{}normal}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{S}\n",
       "\\PY{+w}{            }\\PY{n+nt}{order}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1}\n",
       "\n",
       "\\PY{+w}{  }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{name}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{periodicTurbulentChannelMultilevel}\n",
       "\\PY{+w}{    }\\PY{n+nt}{save\\PYZus{}path}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{./validation/turbulence/02\\PYZus{}turbulent\\PYZus{}channel\\PYZus{}flow/results/}\n",
       "\n",
       "\\PY{+w}{    }\\PY{n+nt}{n\\PYZus{}steps}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{200000}\n",
       "\\PY{+w}{    }\\PY{c+c1}{\\PYZsh{} u* = 0.00525 / l = 48 / ETT = l/u* = 9,150}\n",
       "\\PY{+w}{    }\\PY{c+c1}{\\PYZsh{} Re\\PYZus{}tau = 180}\n",
       "\\PY{+w}{    }\\PY{c+c1}{\\PYZsh{} y+ = 3.75 (lvl 0)}\n",
       "\n",
       "\\PY{+w}{    }\\PY{n+nt}{report}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{n+nt}{frequency}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1000}\n",
       "\n",
       "\\PY{+w}{    }\\PY{n+nt}{domain}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{n+nt}{domain\\PYZus{}size}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{x}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!math}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{\\PYZdl{}\\PYZob{}ds\\PYZus{}2.x\\PYZcb{}}\n",
       "\\PY{+w}{        }\\PY{n+nt}{y}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!math}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{\\PYZdl{}\\PYZob{}ds\\PYZus{}2.y\\PYZcb{}}\n",
       "\\PY{+w}{        }\\PY{n+nt}{z}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!math}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{\\PYZdl{}\\PYZob{}ds\\PYZus{}2.z\\PYZcb{}}\n",
       "\\PY{+w}{      }\\PY{n+nt}{block\\PYZus{}size}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{8}\n",
       "\\PY{+w}{      }\\PY{n+nt}{refinement}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{static}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{default}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{volumes\\PYZus{}refine}\\PY{p}{:}\n",
       "\\PY{+w}{              }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{start}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{0}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{0}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{0}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{                }\\PY{n+nt}{end}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{384}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{8}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{96}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{                }\\PY{n+nt}{lvl}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1}\n",
       "\\PY{+w}{                }\\PY{n+nt}{is\\PYZus{}abs}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{true}\n",
       "\\PY{+w}{              }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{start}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{0}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{88}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{0}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{                }\\PY{n+nt}{end}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{384}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{96}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{96}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{                }\\PY{n+nt}{lvl}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1}\n",
       "\\PY{+w}{                }\\PY{n+nt}{is\\PYZus{}abs}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{true}\n",
       "\n",
       "\\PY{+w}{    }\\PY{n+nt}{data}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{n+nt}{exports}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{default}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{macrs}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{rho}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{u}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{S}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{          }\\PY{n+nt}{interval}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{frequency}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{200000}\n",
       "\\PY{+w}{            }\\PY{n+nt}{lvl}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0}\n",
       "\\PY{+w}{          }\\PY{n+nt}{target}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{volume}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{\\PYZob{}}\\PY{p+pIndicator}{\\PYZcb{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{outputs}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{instantaneous}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{true}\n",
       "\\PY{+w}{        }\\PY{n+nt}{start\\PYZus{}simul}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{macrs}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{rho}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{u}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{S}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{          }\\PY{n+nt}{interval}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{end\\PYZus{}step}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{2000}\n",
       "\\PY{+w}{            }\\PY{n+nt}{frequency}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{500}\n",
       "\\PY{+w}{            }\\PY{n+nt}{lvl}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0}\n",
       "\\PY{+w}{          }\\PY{n+nt}{target}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{volume}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{\\PYZob{}}\\PY{p+pIndicator}{\\PYZcb{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{outputs}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{instantaneous}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{true}\n",
       "\\PY{+w}{        }\\PY{n+nt}{default\\PYZus{}stats}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{macrs}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{rho}\n",
       "\\PY{+w}{            }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{u}\n",
       "\\PY{+w}{          }\\PY{n+nt}{interval}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{frequency}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{50}\n",
       "\\PY{+w}{            }\\PY{n+nt}{start\\PYZus{}step}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{50000}\n",
       "\\PY{+w}{            }\\PY{n+nt}{lvl}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0}\n",
       "\\PY{+w}{          }\\PY{n+nt}{target}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{volume}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{\\PYZob{}}\\PY{p+pIndicator}{\\PYZcb{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{outputs}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{instantaneous}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{false}\n",
       "\\PY{+w}{            }\\PY{n+nt}{stats}\\PY{p}{:}\n",
       "\\PY{+w}{              }\\PY{n+nt}{macrs\\PYZus{}1st\\PYZus{}order}\\PY{p}{:}\n",
       "\\PY{+w}{                }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{rho}\n",
       "\\PY{+w}{                }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{u}\n",
       "\\PY{+w}{              }\\PY{n+nt}{macrs\\PYZus{}2nd\\PYZus{}order}\\PY{p}{:}\n",
       "\\PY{+w}{                }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{u}\n",
       "\\PY{+w}{        }\\PY{n+nt}{plane\\PYZus{}series}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{macrs}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{rho}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{u}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{          }\\PY{n+nt}{interval}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{\\PYZob{}}\\PY{n+nt}{frequency}\\PY{p}{:}\\PY{+w}{ }\\PY{n+nv}{50000}\\PY{p+pIndicator}{,}\\PY{n+nt}{ lvl}\\PY{p}{:}\\PY{+w}{ }\\PY{n+nv}{0}\\PY{p+pIndicator}{\\PYZcb{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{target}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{planes}\\PY{p}{:}\n",
       "\\PY{+w}{              }\\PY{c+c1}{\\PYZsh{} Streamwise / wall\\PYZhy{}normal mid\\PYZhy{}plane (walls are y\\PYZhy{}normal here).}\n",
       "\\PY{+w}{              }\\PY{n+nt}{mid\\PYZus{}channel}\\PY{p}{:}\n",
       "\\PY{+w}{                }\\PY{n+nt}{axis}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{z}\n",
       "\\PY{+w}{                }\\PY{n+nt}{axis\\PYZus{}pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{48}\n",
       "\\PY{+w}{                }\\PY{n+nt}{dist}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1}\n",
       "\\PY{+w}{              }\\PY{c+c1}{\\PYZsh{} Wall\\PYZhy{}parallel plane in the buffer layer (y+ \\PYZti{} 15, inside the}\n",
       "\\PY{+w}{              }\\PY{c+c1}{\\PYZsh{} refined wall block): near\\PYZhy{}wall streak visualization. One node}\n",
       "\\PY{+w}{              }\\PY{c+c1}{\\PYZsh{} apart is enough \\PYZhy{} the streak spacing is \\PYZti{}26 nodes.}\n",
       "\\PY{+w}{              }\\PY{n+nt}{near\\PYZus{}wall}\\PY{p}{:}\n",
       "\\PY{+w}{                }\\PY{n+nt}{axis}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{y}\n",
       "\\PY{+w}{                }\\PY{n+nt}{axis\\PYZus{}pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{4}\n",
       "\\PY{+w}{                }\\PY{n+nt}{dist}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1}\n",
       "\\PY{+w}{          }\\PY{n+nt}{outputs}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{instantaneous}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{true}\n",
       "\n",
       "\\PY{+w}{    }\\PY{n+nt}{models}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{n+nt}{precision}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{default}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{single}\n",
       "\n",
       "\\PY{+w}{      }\\PY{n+nt}{LBM}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{tau}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0.5042}\n",
       "\\PY{+w}{        }\\PY{n+nt}{F}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{x}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{5.75e\\PYZhy{}7}\n",
       "\\PY{+w}{          }\\PY{n+nt}{y}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0}\n",
       "\\PY{+w}{          }\\PY{n+nt}{z}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0}\n",
       "\\PY{+w}{        }\\PY{n+nt}{vel\\PYZus{}set}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{D3Q27}\n",
       "\\PY{+w}{        }\\PY{n+nt}{coll\\PYZus{}oper}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{RRBGK}\n",
       "\\PY{+w}{      }\\PY{n+nt}{initialization}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{equations}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{rho}\\PY{p}{:}\\PY{+w}{ }\\PY{l+s}{\\PYZdq{}}\\PY{l+s}{1}\\PY{l+s}{\\PYZdq{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{ux}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!sub}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{\\PYZdl{}\\PYZob{}init.ds\\PYZus{}2.ux\\PYZcb{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{uy}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!sub}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{\\PYZdl{}\\PYZob{}init.ds\\PYZus{}2.uy\\PYZcb{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{uz}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!sub}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{\\PYZdl{}\\PYZob{}init.ds\\PYZus{}2.uz\\PYZcb{}}\n",
       "\n",
       "\\PY{+w}{      }\\PY{n+nt}{engine}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{name}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{CUDA}\n",
       "\n",
       "\\PY{+w}{      }\\PY{n+nt}{BC}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{periodic\\PYZus{}dims}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{true}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{false}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{true}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{        }\\PY{n+nt}{BC\\PYZus{}map}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{N}\n",
       "\\PY{+w}{            }\\PY{n+nt}{BC}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{RegularizedHWBB}\n",
       "\\PY{+w}{            }\\PY{n+nt}{wall\\PYZus{}normal}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{N}\n",
       "\\PY{+w}{            }\\PY{n+nt}{order}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1}\n",
       "\n",
       "\\PY{+w}{          }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{S}\n",
       "\\PY{+w}{            }\\PY{n+nt}{BC}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{RegularizedHWBB}\n",
       "\\PY{+w}{            }\\PY{n+nt}{wall\\PYZus{}normal}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{S}\n",
       "\\PY{+w}{            }\\PY{n+nt}{order}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1}\n",
       "\\end{Verbatim}\n"
      ],
      "text/plain": [
       "variables:\n",
       "  # Domain size\n",
       "  ds_1:\n",
       "    x: 512\n",
       "    y: 128\n",
       "    z: 128\n",
       "  ds_2:\n",
       "    x: 384\n",
       "    y: 96\n",
       "    z: 96\n",
       "\n",
       "  # Equation-based (\"cold\") start - self-contained, no external\n",
       "  # artefact. The streamwise field is an analytic Reichardt mean\n",
       "  # profile mirrored across both walls (wall distance in viscous\n",
       "  # units y+ = (u*/nu) * min(y, NY - y)), scaled by the friction\n",
       "  # velocity u*, seeded with wall-enveloped multi-mode sinusoidal\n",
       "  # perturbations (streamwise streaks plus cross-flow rolls carrying\n",
       "  # wall-normal velocity) at ~10% intensity to break the x/z symmetry\n",
       "  # and trip transition to turbulence. The sin(pi*y/NY) envelope\n",
       "  # vanishes at both no-slip walls. The scalar is initialised\n",
       "  # separately via its `initial_field` ramp.\n",
       "  #\n",
       "  # Per-domain friction velocity u* and inner-scale coefficient\n",
       "  # y+/lattice = u*/nu, with nu = cs^2 (tau - 0.5):\n",
       "  #   ds_1: Re_tau 142, tau=0.5074 -> nu=2.467e-3, u*=0.0054962, u*/nu=2.228\n",
       "  #   ds_2: Re_tau 180, tau=0.5042 -> nu=1.400e-3, u*=0.00525, u*/nu=3.75\n",
       "  us_1: 0.0054962\n",
       "  yp_1: 2.228\n",
       "  us_2: 0.00525\n",
       "  yp_2: 3.75\n",
       "  init:\n",
       "    ds_1:\n",
       "      ux: !sub \"${us_1} * (2.5*log(1 + 0.41*${yp_1}*min(y, ${ds_1.y} - y)) + 7.8*(1 - exp(-${yp_1}*min(y, ${ds_1.y} - y)/11) - (${yp_1}*min(y, ${ds_1.y} - y)/11)*exp(-${yp_1}*min(y, ${ds_1.y} - y)/3))) + 0.010*sin(pi*y/${ds_1.y})*cos(2*pi*5*z/${ds_1.z}) + 0.006*sin(pi*y/${ds_1.y})*sin(2*pi*3*x/${ds_1.x})*cos(2*pi*4*z/${ds_1.z})\"\n",
       "      uy: !sub \"0.006*sin(pi*y/${ds_1.y})*sin(2*pi*3*x/${ds_1.x})*cos(2*pi*4*z/${ds_1.z}) + 0.004*sin(pi*y/${ds_1.y})*sin(2*pi*2*x/${ds_1.x})*sin(2*pi*3*z/${ds_1.z})\"\n",
       "      uz: !sub \"0.006*sin(pi*y/${ds_1.y})*sin(2*pi*3*x/${ds_1.x})*sin(2*pi*4*z/${ds_1.z}) - 0.004*sin(pi*y/${ds_1.y})*cos(2*pi*2*x/${ds_1.x})*cos(2*pi*3*z/${ds_1.z})\"\n",
       "    ds_2:\n",
       "      ux: !sub \"${us_2} * (2.5*log(1 + 0.41*${yp_2}*min(y, ${ds_2.y} - y)) + 7.8*(1 - exp(-${yp_2}*min(y, ${ds_2.y} - y)/11) - (${yp_2}*min(y, ${ds_2.y} - y)/11)*exp(-${yp_2}*min(y, ${ds_2.y} - y)/3))) + 0.010*sin(pi*y/${ds_2.y})*cos(2*pi*5*z/${ds_2.z}) + 0.006*sin(pi*y/${ds_2.y})*sin(2*pi*3*x/${ds_2.x})*cos(2*pi*4*z/${ds_2.z})\"\n",
       "      uy: !sub \"0.006*sin(pi*y/${ds_2.y})*sin(2*pi*3*x/${ds_2.x})*cos(2*pi*4*z/${ds_2.z}) + 0.004*sin(pi*y/${ds_2.y})*sin(2*pi*2*x/${ds_2.x})*sin(2*pi*3*z/${ds_2.z})\"\n",
       "      uz: !sub \"0.006*sin(pi*y/${ds_2.y})*sin(2*pi*3*x/${ds_2.x})*sin(2*pi*4*z/${ds_2.z}) - 0.004*sin(pi*y/${ds_2.y})*cos(2*pi*2*x/${ds_2.x})*cos(2*pi*3*z/${ds_2.z})\"\n",
       "\n",
       "simulations:\n",
       "  - name: periodicTurbulentChannel\n",
       "    save_path: ./validation/turbulence/02_turbulent_channel_flow/results/\n",
       "\n",
       "    n_steps: 600000\n",
       "    report:\n",
       "      frequency: 1000\n",
       "\n",
       "    domain:\n",
       "      # u* = 0.0054962 / l = 64 / ETT = l/u* = 11,644\n",
       "      # Re_tau = 142\n",
       "      # y+ = 2.228\n",
       "      domain_size:\n",
       "        x: !math ${ds_1.x}\n",
       "        y: !math ${ds_1.y}\n",
       "        z: !math ${ds_1.z}\n",
       "      block_size: 8\n",
       "\n",
       "    data:\n",
       "      exports:\n",
       "        default:\n",
       "          macrs: [rho, u, S]\n",
       "          interval:\n",
       "            frequency: 200000\n",
       "            lvl: 0\n",
       "          target:\n",
       "            volume: {}\n",
       "          outputs:\n",
       "            instantaneous: true\n",
       "        default_stats:\n",
       "          macrs:\n",
       "            - rho\n",
       "            - u\n",
       "          interval:\n",
       "            frequency: 100\n",
       "            start_step: 300000\n",
       "            lvl: 0\n",
       "          target:\n",
       "            volume: {}\n",
       "          outputs:\n",
       "            instantaneous: false\n",
       "            stats:\n",
       "              macrs_1st_order:\n",
       "                - rho\n",
       "                - u\n",
       "              macrs_2nd_order:\n",
       "                - u\n",
       "        plane_series:\n",
       "          macrs: [rho, u]\n",
       "          interval: {frequency: 50000, lvl: 0}\n",
       "          target:\n",
       "            planes:\n",
       "              # Streamwise / wall-normal mid-plane (walls are y-normal here).\n",
       "              mid_channel:\n",
       "                axis: z\n",
       "                axis_pos: 64\n",
       "                dist: 1\n",
       "              # Wall-parallel plane in the buffer layer (y+ ~ 16):\n",
       "              # near-wall streak visualization.\n",
       "              near_wall:\n",
       "                axis: y\n",
       "                axis_pos: 8\n",
       "                dist: 1\n",
       "          outputs:\n",
       "            instantaneous: true\n",
       "\n",
       "    models:\n",
       "      precision:\n",
       "        default: single\n",
       "\n",
       "      LBM:\n",
       "        tau: 0.5074\n",
       "        F:\n",
       "          x: 4.72e-7\n",
       "          y: 0\n",
       "          z: 0\n",
       "        vel_set: D3Q27\n",
       "        coll_oper: RRBGK\n",
       "      initialization:\n",
       "        equations:\n",
       "          rho: \"1\"\n",
       "          ux: !sub ${init.ds_1.ux}\n",
       "          uy: !sub ${init.ds_1.uy}\n",
       "          uz: !sub ${init.ds_1.uz}\n",
       "\n",
       "      engine:\n",
       "        name: CUDA\n",
       "\n",
       "      BC:\n",
       "        periodic_dims: [true, false, true]\n",
       "        BC_map:\n",
       "          - pos: N\n",
       "            BC: RegularizedHWBB\n",
       "            wall_normal: N\n",
       "            order: 1\n",
       "\n",
       "          - pos: S\n",
       "            BC: RegularizedHWBB\n",
       "            wall_normal: S\n",
       "            order: 1\n",
       "\n",
       "  - name: periodicTurbulentChannelMultilevel\n",
       "    save_path: ./validation/turbulence/02_turbulent_channel_flow/results/\n",
       "\n",
       "    n_steps: 200000\n",
       "    # u* = 0.00525 / l = 48 / ETT = l/u* = 9,150\n",
       "    # Re_tau = 180\n",
       "    # y+ = 3.75 (lvl 0)\n",
       "\n",
       "    report:\n",
       "      frequency: 1000\n",
       "\n",
       "    domain:\n",
       "      domain_size:\n",
       "        x: !math ${ds_2.x}\n",
       "        y: !math ${ds_2.y}\n",
       "        z: !math ${ds_2.z}\n",
       "      block_size: 8\n",
       "      refinement:\n",
       "        static:\n",
       "          default:\n",
       "            volumes_refine:\n",
       "              - start: [0, 0, 0]\n",
       "                end: [384, 8, 96]\n",
       "                lvl: 1\n",
       "                is_abs: true\n",
       "              - start: [0, 88, 0]\n",
       "                end: [384, 96, 96]\n",
       "                lvl: 1\n",
       "                is_abs: true\n",
       "\n",
       "    data:\n",
       "      exports:\n",
       "        default:\n",
       "          macrs: [rho, u, S]\n",
       "          interval:\n",
       "            frequency: 200000\n",
       "            lvl: 0\n",
       "          target:\n",
       "            volume: {}\n",
       "          outputs:\n",
       "            instantaneous: true\n",
       "        start_simul:\n",
       "          macrs: [rho, u, S]\n",
       "          interval:\n",
       "            end_step: 2000\n",
       "            frequency: 500\n",
       "            lvl: 0\n",
       "          target:\n",
       "            volume: {}\n",
       "          outputs:\n",
       "            instantaneous: true\n",
       "        default_stats:\n",
       "          macrs:\n",
       "            - rho\n",
       "            - u\n",
       "          interval:\n",
       "            frequency: 50\n",
       "            start_step: 50000\n",
       "            lvl: 0\n",
       "          target:\n",
       "            volume: {}\n",
       "          outputs:\n",
       "            instantaneous: false\n",
       "            stats:\n",
       "              macrs_1st_order:\n",
       "                - rho\n",
       "                - u\n",
       "              macrs_2nd_order:\n",
       "                - u\n",
       "        plane_series:\n",
       "          macrs: [rho, u]\n",
       "          interval: {frequency: 50000, lvl: 0}\n",
       "          target:\n",
       "            planes:\n",
       "              # Streamwise / wall-normal mid-plane (walls are y-normal here).\n",
       "              mid_channel:\n",
       "                axis: z\n",
       "                axis_pos: 48\n",
       "                dist: 1\n",
       "              # Wall-parallel plane in the buffer layer (y+ ~ 15, inside the\n",
       "              # refined wall block): near-wall streak visualization. One node\n",
       "              # apart is enough - the streak spacing is ~26 nodes.\n",
       "              near_wall:\n",
       "                axis: y\n",
       "                axis_pos: 4\n",
       "                dist: 1\n",
       "          outputs:\n",
       "            instantaneous: true\n",
       "\n",
       "    models:\n",
       "      precision:\n",
       "        default: single\n",
       "\n",
       "      LBM:\n",
       "        tau: 0.5042\n",
       "        F:\n",
       "          x: 5.75e-7\n",
       "          y: 0\n",
       "          z: 0\n",
       "        vel_set: D3Q27\n",
       "        coll_oper: RRBGK\n",
       "      initialization:\n",
       "        equations:\n",
       "          rho: \"1\"\n",
       "          ux: !sub ${init.ds_2.ux}\n",
       "          uy: !sub ${init.ds_2.uy}\n",
       "          uz: !sub ${init.ds_2.uz}\n",
       "\n",
       "      engine:\n",
       "        name: CUDA\n",
       "\n",
       "      BC:\n",
       "        periodic_dims: [true, false, true]\n",
       "        BC_map:\n",
       "          - pos: N\n",
       "            BC: RegularizedHWBB\n",
       "            wall_normal: N\n",
       "            order: 1\n",
       "\n",
       "          - pos: S\n",
       "            BC: RegularizedHWBB\n",
       "            wall_normal: S\n",
       "            order: 1"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Code\n",
    "\n",
    "Code(filename=filename)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "nassu",
   "language": "python",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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